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Kuraklık Riskinin Bulanık Mantık Yardımıyla Türkiye Genelinde Değerlendirilmesi

Year 2019, , 359 - 372, 15.03.2019
https://doi.org/10.24012/dumf.499660

Abstract

Bu
çalışmada meteorolojik ve sosyo-ekonomik veriler kullanılarak elde edilen
kuraklık afet ve hassasiyetlik göstergeleri yardımıyla Türkiye genelinde
kuraklık riski bulanık mantık çıkarımı (BMÇ) yaklaşımıyla bütüncül olarak
değerlendirilmiştir. Kuraklık afetinin tam olarak anlaşılmasında kuraklık risk
ve hassasiyetinin önemi bilinse de Türkiye için bütüncül ve yeterli miktarda
bilimsel çalışmanın varlığından bahsetmek zordur. Kuraklık Afet Göstergesi
(KAG) kuraklığın görülme ihtimaline dayanan standart yağış göstergesi (SYG)
(Standardized Precipitation Index-SPI) kullanılarak kuraklık kavramının daha
iyi anlaşılmasını kolaylaştırmak için hesaplanmıştır. Bunun yanında, Kuraklık
Hassasiyet Göstergesi (KHG) kuraklığın sonuçlarının bağlı olduğu güncel dört
adet sosyo-ekonomik veri kullanılarak hesaplanmıştır. BMÇ yardımıyla kuraklık
afet ve hassasiyet göstergelerinin, kuraklık riskinin belirlenmesindeki
öneminin vurgulanması bu çalışmanın temel hedefidir. Çalışma sonucunda elde
edilen bulgulara göre Türkiye genelinde 81 il arasında 5 ilin düşük kuraklık
riski taşıdığı, 61 ilin orta kuraklık riskine sahip olduğu, 14 ilde yüksek
kuraklık riskinin bulunduğu ve son olarak sadece Konya’da çok yüksek kuraklık
riski ortaya çıktığı tespit edilmiştir.

References

  • Awange, J. L., Mpelasoka, F., Goncalves, R. M., Science of the Total Environment When every drop counts: Analysis of Droughts in Brazil for the 1901-2013 period. Science of the Total Environment, 566–567, 1472–1488, 2016. http://doi.org/10.1016/j.scitotenv.2016.06.031
  • Bates, B. C., Kundzewicz, Z. W., Wu, S., Palutikof (Eds.) J. P., Climate Change and Water, Tech. Pap. VI, Intergovernmental Panel on Clim. Change, Geneva, Switzerland, 2008.
  • Brooks, N., Adger, W., Kelly, P., The determinants of vulnerability and adaptive capacity at the national level and the implications for adaptation. Glob. Environ. Change 15, 151-163, 2005.
  • Dabanlı, İ., Mishra A.K., Şen, Z., "Long-term spatio-temporal drought variability in Turkey." Journal of Hydrology 552: 779-792, 2017. https://doi.org/10.1016/j.jhydrol.2017.07.038
  • Dabanlı, İ., Şen, Z., Yeleğen, M. Ö., Şişman, E., Selek, B., Güçlü, Y. S., Trend Assessment by the Innovative-Şen Method. Water Resources Management, 30(14), 5193–5203, 2016. http://doi.org/10.1007/s11269-016-1478-4.
  • Dahal, P., Shrestha, N. S., Shrestha, M. L., Krakauer, N. Y., Panthi, J., Pradhanang, S. M., … Lakhankar, T., Drought risk assessment in central Nepal: temporal and spatial analysis. Natural Hazards, 80(3), 1913–1932, 2015. http://doi.org/10.1007/s11069-015-2055-5
  • Dai, A., Drought under global warming: A review. Wiley Interdisciplinary Reviews: Climate Change, 2(1), 45–65, 2011. http://doi.org/10.1002/wcc.81
  • Eakin, H., Conley, J., Climate variability and the vulnerability of ranching in southeastern Arizona: a pilot study. Clim. Res. 21, 271-282, 2002.
  • Ekrami, M., Fatehi, A., Jalal, M., Drought vulnerability mapping using AHP method in arid and semiarid areas: a case study for Taft Township, Yazd. Environmental Earth Sciences, 75(12), 1–13, 2016. http://doi.org/10.1007/s12665-016-5822-z
  • Fontaine, M. M., Steinemann, A. C., Assessing vulnerability to natural hazards: impact-based method and application to drought in Washington state. Nat. Hazards Review. NHR 10, 11-18, 2009.
  • Gampe, D., Ludwig, R., Qahman, K., Afifi, S., Applying the Triangle Method for the parameterization of irrigated areas as input for spatially distributed hydrological modeling- Assessing future drought risk in the Gaza Strip (Palestine). Science of the Total Environment, 543, 877–888, 2016. http://doi.org/10.1016/j.scitotenv.2015.07.098
  • Guttman, N. B., Accepting the Standardized Precipitation Index: a Calculation Algorithm1. JAWRA Journal of the American Water Resources Association, 35(2), 311–322, 1999. http://doi:10.1111/j.1752-1688.1999.tb03592.x
  • Güçlü, Y. S., Şen, Z., Hydrograph estimation with fuzzy chain model, 538, 587–597, 2016. http://doi.org/10.1016/j.jhydrol.2016.04.057
  • Hao, Z., AghaKouchak, A., Multivariate standardized drought index: a parametric multi-index model. Adv. Water Resour. 57, 12–18, 2013.
  • Jia, H., Wang, D. P. J., Risk mapping of integrated natural disasters in China. Natural Hazards, 80(3), 2023–2035, 2016. http://doi.org/10.1007/s11069-015-2057-3.
  • Jin, J., Wang, W., Wang, X., Adapting agriculture to the drought hazard in rural China: household strategies and determinants. Natural Hazards, 82(3), 1609–1619, 2016. http://doi.org/10.1007/s11069-016-2260-x
  • Kao, S. C., Govindaraju, R. S., A copula-based joint deficit index for droughts. J. Hydrol. 380 (1–2), 121–134, 2010.
  • Kim, D. W., Byun, H. R., Choi, K. S., Oh, S. B., A spatiotemporal analysis of historical droughts in Korea. J. Appl. Meteorol. Clim. 50, 1895-1912, 2011.
  • Kim, H., Park, J., Yoo, J., Kim, T. Assessment of drought hazard, vulnerability, and risk: A case study for administrative districts in South Korea. Journal of Hydro-Environment Research, 9(1), 28–35, 2015. http://doi.org/10.1016/j.jher.2013.07.003
  • Lin, M. L., Chu, C. M., Tsai, B. W., Drought risk assessment in western Inner-Mongolia. Int. J. Environ. Res. 5(1), 139-148, 2011.
  • Mamdani, E. H., Assilian S., An experiment in linguistic synthesis with a fuzzy logic controller, International Journal of Man-Machine Studies, 7(1), 1-13, 1975.
  • McKee, T. B., Doesken, N. J., Kleist, J., The relationship of drought frequency and duration time scales. In: Eighth Conference on Applied Climatology. American Meteorological Society, Anaheim, California, 1993.
  • Metzger, M. J., Leemans, R., Schr€oter, D., A multidisciplinary multiscale framework for assessing vulnerabilities to global change. Int. J. Appl. Earth Obs. 7, 253-267, 2005.
  • Mishra, A. K., Desai, V. R., Spatial and temporal drought analysis in the Kansabati river basin, India. International Journal of River Basin Management, 3(1), 31–41, 2005. http://doi.org/10.1080/15715124.2005.9635243.
  • Mishra, A. K., Singh, V. P., A review of drought concepts. Journal of Hydrology, 391(1-2), 202–216, 2010. http://doi.org/10.1016/j.jhydrol.2010.07.012
  • Nam, W., Hayes, M. J., Svoboda, M. D., Tadesse, T., Wilhite, D. A., Drought hazard assessment in the context of climate change for South Korea. Agricultural Water Management, 160, 106–117, 2015. http://doi.org/10.1016/j.agwat.2015.06.029
  • Pei, W., Fu, Q., Li, D. L. T., Assessing agricultural drought vulnerability in the Sanjiang Plain based on an improved projection pursuit model. Natural Hazards, 82(1), 683–701, 2016. http://doi.org/10.1007/s11069-016-2213-4
  • Rahman, R., Lateh, H., Meteorological drought in Bangladesh: assessing, analyzing and hazard mapping using SPI, GIS and monthly rainfall data. Environmental Earth Sciences, 75(12), 1–20, 2016. http://doi.org/10.1007/s12665-016-5829-5
  • Rajsekhar, D., Singh, V. P., Mishra, A. K., Integrated drought causality, hazard, and vulnerability assessment for future socioeconomic scenarios: An information theory perspective, 6346–6378, 2015. http://doi.org/10.1002/2014JD022670.
  • Santos, F., Pulido-calvo, I., Portela, M. M., Spatial and temporal variability of droughts in Portugal, 46, 1–13, 2010. http://doi.org/10.1029/2009WR008071.
  • Sarhadi, A., Burn, D. H., Ausin, M. C. Wiper, M. P., Time-varying nonstationary multivariate risk analysis using a dynamic Bayesian copula, Water Resour. Res., 52, 2327–2349, 2016. http://doi.org/10.1002/2015WR018525.
  • Shahid, S., Behrawan, H., Drought risk assessment in the western part of Bangladesh. Nat. Hazards, 46, 391-413, 2008.
  • Şen, Z., Wet and dry periods of annual flow series. Journal of Hydrology, 102, 1503–1514, 1976.
  • Şen, Z., Autorun analysis of hydrological time series. Journal of Hydrology, 36, 75–85, 1978.
  • Şen, Z., Probabilistic formulation of spatio-temporal drought pattern. Theoretical and Applied Climatology, 61(3-4), 197–206, 1998. http://doi.org/10.1007/s007040050064
  • Şen, Z., Fuzzy logic and system models in water sciences. Turkish Water Foundation, İstanbul, 2004.
  • Şen, Z., Applied Drought Modeling, Prediction, and Mitigation, 1st Edition, Elsevier, Amsterdam, 2015.
  • Toprak, Z.F., Flow Discharge Modeling in Open Canals Using a New Fuzzy Modeling Technique (SMRGT), Clean-Soil Air Water 37(9): 742-752, 2009.
  • Tosunoglu, F., Can, I., Application of copulas for regional bivariate frequency analysis of meteorological droughts in Turkey. Natural Hazards, 82(3), 1457–1477, 2016. http://doi.org/10.1007/s11069-016-2253-9
  • Tsakiris, G., Pangalou, D., Vangelis, H., Regional drought assessment based on the Reconnaissance Drought Index (RDI). Water Resour. Manage. 21(5), 821–833, 2007.
  • UNDP, United Nation Development Program, Reducing Disaster Risk: a Challenge for Development. John S. Swift Co, New York, 2004.
  • Vasiliades, L., Loukas, A., Hydrological response to meteorological drought using the Palmer drought indices in Thessaly, Greece. Desalination, 237(1–3), 3–21, 2009. http://doi.org/10.1016/j.desal.2007.12.019
  • Venkataraman, K., Tummuri, S., Medina, A., Perry, J., 21st century drought outlook for major climate divisions of Texas based on CMIP5 multimodel ensemble: Implications for water resource management. Journal of Hydrology, 534, 300–316, 2016. http://doi.org/10.1016/j.jhydrol.2016.01.001
  • Verdon-Kidd, D. C., Kiem, A. S., Quantifying drought risk in a nonstationary climate. J. Hydrometeorol., 11, 1019-1031, 2010.
  • Vicente-Serrano, S. M., Spatial and temporal analysis of droughts in the Iberian Peninsula (1910– 2000), Hydrol. Sci. J., 51(1), 83–97, 2006. http://doi.org/10.1623/hysj.51.1.83.
  • Vicente-Serrano, S. M., Begueria, S., Lopez-Moreno, J. I., A multiscalar drought index sensitive to global warming: the standardized precipitation evapotranspiration index. J. Climate 23(7), 1696–1718, 2010.
  • Wang, Y., Zhang, Q., Singh, V. P., Spatiotemporal patterns of precipitation regimes in the Huai River basin, China, and possible relations with ENSO events. Natural Hazards, 82(3), 2167–2185, 2016. http://doi.org/10.1007/s11069-016-2303-3
  • Wilhite, D., Drought: A Global Assessment, Vol. I, pp. 3–18, London: Routledge, 2000.
  • Wilhelmi, O. V., Wilhite, D. A., Assessing vulnerability to agricultural drought: a Nebraska case study. Nat. Hazards, 25, 37-58, 2002.
  • Xu, K., Yang, D., Yang, H., Li, Z., Qin, Y., Shen, Y., Spatio-temporal variation of drought in China during 1961-2012: A climatic perspective. Journal of Hydrology, 526(7), 253–264, 2015. http://doi.org/10.1016/j.jhydrol.2014.09.047
Year 2019, , 359 - 372, 15.03.2019
https://doi.org/10.24012/dumf.499660

Abstract

References

  • Awange, J. L., Mpelasoka, F., Goncalves, R. M., Science of the Total Environment When every drop counts: Analysis of Droughts in Brazil for the 1901-2013 period. Science of the Total Environment, 566–567, 1472–1488, 2016. http://doi.org/10.1016/j.scitotenv.2016.06.031
  • Bates, B. C., Kundzewicz, Z. W., Wu, S., Palutikof (Eds.) J. P., Climate Change and Water, Tech. Pap. VI, Intergovernmental Panel on Clim. Change, Geneva, Switzerland, 2008.
  • Brooks, N., Adger, W., Kelly, P., The determinants of vulnerability and adaptive capacity at the national level and the implications for adaptation. Glob. Environ. Change 15, 151-163, 2005.
  • Dabanlı, İ., Mishra A.K., Şen, Z., "Long-term spatio-temporal drought variability in Turkey." Journal of Hydrology 552: 779-792, 2017. https://doi.org/10.1016/j.jhydrol.2017.07.038
  • Dabanlı, İ., Şen, Z., Yeleğen, M. Ö., Şişman, E., Selek, B., Güçlü, Y. S., Trend Assessment by the Innovative-Şen Method. Water Resources Management, 30(14), 5193–5203, 2016. http://doi.org/10.1007/s11269-016-1478-4.
  • Dahal, P., Shrestha, N. S., Shrestha, M. L., Krakauer, N. Y., Panthi, J., Pradhanang, S. M., … Lakhankar, T., Drought risk assessment in central Nepal: temporal and spatial analysis. Natural Hazards, 80(3), 1913–1932, 2015. http://doi.org/10.1007/s11069-015-2055-5
  • Dai, A., Drought under global warming: A review. Wiley Interdisciplinary Reviews: Climate Change, 2(1), 45–65, 2011. http://doi.org/10.1002/wcc.81
  • Eakin, H., Conley, J., Climate variability and the vulnerability of ranching in southeastern Arizona: a pilot study. Clim. Res. 21, 271-282, 2002.
  • Ekrami, M., Fatehi, A., Jalal, M., Drought vulnerability mapping using AHP method in arid and semiarid areas: a case study for Taft Township, Yazd. Environmental Earth Sciences, 75(12), 1–13, 2016. http://doi.org/10.1007/s12665-016-5822-z
  • Fontaine, M. M., Steinemann, A. C., Assessing vulnerability to natural hazards: impact-based method and application to drought in Washington state. Nat. Hazards Review. NHR 10, 11-18, 2009.
  • Gampe, D., Ludwig, R., Qahman, K., Afifi, S., Applying the Triangle Method for the parameterization of irrigated areas as input for spatially distributed hydrological modeling- Assessing future drought risk in the Gaza Strip (Palestine). Science of the Total Environment, 543, 877–888, 2016. http://doi.org/10.1016/j.scitotenv.2015.07.098
  • Guttman, N. B., Accepting the Standardized Precipitation Index: a Calculation Algorithm1. JAWRA Journal of the American Water Resources Association, 35(2), 311–322, 1999. http://doi:10.1111/j.1752-1688.1999.tb03592.x
  • Güçlü, Y. S., Şen, Z., Hydrograph estimation with fuzzy chain model, 538, 587–597, 2016. http://doi.org/10.1016/j.jhydrol.2016.04.057
  • Hao, Z., AghaKouchak, A., Multivariate standardized drought index: a parametric multi-index model. Adv. Water Resour. 57, 12–18, 2013.
  • Jia, H., Wang, D. P. J., Risk mapping of integrated natural disasters in China. Natural Hazards, 80(3), 2023–2035, 2016. http://doi.org/10.1007/s11069-015-2057-3.
  • Jin, J., Wang, W., Wang, X., Adapting agriculture to the drought hazard in rural China: household strategies and determinants. Natural Hazards, 82(3), 1609–1619, 2016. http://doi.org/10.1007/s11069-016-2260-x
  • Kao, S. C., Govindaraju, R. S., A copula-based joint deficit index for droughts. J. Hydrol. 380 (1–2), 121–134, 2010.
  • Kim, D. W., Byun, H. R., Choi, K. S., Oh, S. B., A spatiotemporal analysis of historical droughts in Korea. J. Appl. Meteorol. Clim. 50, 1895-1912, 2011.
  • Kim, H., Park, J., Yoo, J., Kim, T. Assessment of drought hazard, vulnerability, and risk: A case study for administrative districts in South Korea. Journal of Hydro-Environment Research, 9(1), 28–35, 2015. http://doi.org/10.1016/j.jher.2013.07.003
  • Lin, M. L., Chu, C. M., Tsai, B. W., Drought risk assessment in western Inner-Mongolia. Int. J. Environ. Res. 5(1), 139-148, 2011.
  • Mamdani, E. H., Assilian S., An experiment in linguistic synthesis with a fuzzy logic controller, International Journal of Man-Machine Studies, 7(1), 1-13, 1975.
  • McKee, T. B., Doesken, N. J., Kleist, J., The relationship of drought frequency and duration time scales. In: Eighth Conference on Applied Climatology. American Meteorological Society, Anaheim, California, 1993.
  • Metzger, M. J., Leemans, R., Schr€oter, D., A multidisciplinary multiscale framework for assessing vulnerabilities to global change. Int. J. Appl. Earth Obs. 7, 253-267, 2005.
  • Mishra, A. K., Desai, V. R., Spatial and temporal drought analysis in the Kansabati river basin, India. International Journal of River Basin Management, 3(1), 31–41, 2005. http://doi.org/10.1080/15715124.2005.9635243.
  • Mishra, A. K., Singh, V. P., A review of drought concepts. Journal of Hydrology, 391(1-2), 202–216, 2010. http://doi.org/10.1016/j.jhydrol.2010.07.012
  • Nam, W., Hayes, M. J., Svoboda, M. D., Tadesse, T., Wilhite, D. A., Drought hazard assessment in the context of climate change for South Korea. Agricultural Water Management, 160, 106–117, 2015. http://doi.org/10.1016/j.agwat.2015.06.029
  • Pei, W., Fu, Q., Li, D. L. T., Assessing agricultural drought vulnerability in the Sanjiang Plain based on an improved projection pursuit model. Natural Hazards, 82(1), 683–701, 2016. http://doi.org/10.1007/s11069-016-2213-4
  • Rahman, R., Lateh, H., Meteorological drought in Bangladesh: assessing, analyzing and hazard mapping using SPI, GIS and monthly rainfall data. Environmental Earth Sciences, 75(12), 1–20, 2016. http://doi.org/10.1007/s12665-016-5829-5
  • Rajsekhar, D., Singh, V. P., Mishra, A. K., Integrated drought causality, hazard, and vulnerability assessment for future socioeconomic scenarios: An information theory perspective, 6346–6378, 2015. http://doi.org/10.1002/2014JD022670.
  • Santos, F., Pulido-calvo, I., Portela, M. M., Spatial and temporal variability of droughts in Portugal, 46, 1–13, 2010. http://doi.org/10.1029/2009WR008071.
  • Sarhadi, A., Burn, D. H., Ausin, M. C. Wiper, M. P., Time-varying nonstationary multivariate risk analysis using a dynamic Bayesian copula, Water Resour. Res., 52, 2327–2349, 2016. http://doi.org/10.1002/2015WR018525.
  • Shahid, S., Behrawan, H., Drought risk assessment in the western part of Bangladesh. Nat. Hazards, 46, 391-413, 2008.
  • Şen, Z., Wet and dry periods of annual flow series. Journal of Hydrology, 102, 1503–1514, 1976.
  • Şen, Z., Autorun analysis of hydrological time series. Journal of Hydrology, 36, 75–85, 1978.
  • Şen, Z., Probabilistic formulation of spatio-temporal drought pattern. Theoretical and Applied Climatology, 61(3-4), 197–206, 1998. http://doi.org/10.1007/s007040050064
  • Şen, Z., Fuzzy logic and system models in water sciences. Turkish Water Foundation, İstanbul, 2004.
  • Şen, Z., Applied Drought Modeling, Prediction, and Mitigation, 1st Edition, Elsevier, Amsterdam, 2015.
  • Toprak, Z.F., Flow Discharge Modeling in Open Canals Using a New Fuzzy Modeling Technique (SMRGT), Clean-Soil Air Water 37(9): 742-752, 2009.
  • Tosunoglu, F., Can, I., Application of copulas for regional bivariate frequency analysis of meteorological droughts in Turkey. Natural Hazards, 82(3), 1457–1477, 2016. http://doi.org/10.1007/s11069-016-2253-9
  • Tsakiris, G., Pangalou, D., Vangelis, H., Regional drought assessment based on the Reconnaissance Drought Index (RDI). Water Resour. Manage. 21(5), 821–833, 2007.
  • UNDP, United Nation Development Program, Reducing Disaster Risk: a Challenge for Development. John S. Swift Co, New York, 2004.
  • Vasiliades, L., Loukas, A., Hydrological response to meteorological drought using the Palmer drought indices in Thessaly, Greece. Desalination, 237(1–3), 3–21, 2009. http://doi.org/10.1016/j.desal.2007.12.019
  • Venkataraman, K., Tummuri, S., Medina, A., Perry, J., 21st century drought outlook for major climate divisions of Texas based on CMIP5 multimodel ensemble: Implications for water resource management. Journal of Hydrology, 534, 300–316, 2016. http://doi.org/10.1016/j.jhydrol.2016.01.001
  • Verdon-Kidd, D. C., Kiem, A. S., Quantifying drought risk in a nonstationary climate. J. Hydrometeorol., 11, 1019-1031, 2010.
  • Vicente-Serrano, S. M., Spatial and temporal analysis of droughts in the Iberian Peninsula (1910– 2000), Hydrol. Sci. J., 51(1), 83–97, 2006. http://doi.org/10.1623/hysj.51.1.83.
  • Vicente-Serrano, S. M., Begueria, S., Lopez-Moreno, J. I., A multiscalar drought index sensitive to global warming: the standardized precipitation evapotranspiration index. J. Climate 23(7), 1696–1718, 2010.
  • Wang, Y., Zhang, Q., Singh, V. P., Spatiotemporal patterns of precipitation regimes in the Huai River basin, China, and possible relations with ENSO events. Natural Hazards, 82(3), 2167–2185, 2016. http://doi.org/10.1007/s11069-016-2303-3
  • Wilhite, D., Drought: A Global Assessment, Vol. I, pp. 3–18, London: Routledge, 2000.
  • Wilhelmi, O. V., Wilhite, D. A., Assessing vulnerability to agricultural drought: a Nebraska case study. Nat. Hazards, 25, 37-58, 2002.
  • Xu, K., Yang, D., Yang, H., Li, Z., Qin, Y., Shen, Y., Spatio-temporal variation of drought in China during 1961-2012: A climatic perspective. Journal of Hydrology, 526(7), 253–264, 2015. http://doi.org/10.1016/j.jhydrol.2014.09.047
There are 50 citations in total.

Details

Primary Language Turkish
Journal Section Articles
Authors

İsmail Dabanlı 0000-0003-3108-8167

Publication Date March 15, 2019
Submission Date December 19, 2018
Published in Issue Year 2019

Cite

IEEE İ. Dabanlı, “Kuraklık Riskinin Bulanık Mantık Yardımıyla Türkiye Genelinde Değerlendirilmesi”, DÜMF MD, vol. 10, no. 1, pp. 359–372, 2019, doi: 10.24012/dumf.499660.
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